Bayesian Reciprocal Adaptive Bridge Composite Quantile Regression with Ordinal Data
| المصدر: | مجلة القادسية للعلوم الإدارية والاقتصادية |
|---|---|
| الناشر: | جامعة القادسية - كلية الادارة والاقتصاد |
| المؤلف الرئيسي: | Alhamzawi, Rahim (Author) |
| مؤلفين آخرين: | Al-Saadi, Zahraa Yusif Abbas (Co-Author) |
| المجلد/العدد: | مج25, ع4 |
| محكمة: | نعم |
| الدولة: |
العراق |
| التاريخ الميلادي: |
2023
|
| الصفحات: | 267 - 275 |
| ISSN: |
1816-9171 |
| رقم MD: | 1526818 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| كلمات المؤلف المفتاحية: |
Reciprocal Adaptive Bridge | Composite Quantile Regression | Gibbs Sampler | Ordinal Data
|
| رابط المحتوى: |
الناشر لهذه المادة لم يسمح بإتاحتها. |
| LEADER | 02656nam a22002297a 4500 | ||
|---|---|---|---|
| 001 | 2270027 | ||
| 041 | |a eng | ||
| 044 | |b العراق | ||
| 100 | |a Alhamzawi, Rahim |e Author |9 809990 | ||
| 245 | |a Bayesian Reciprocal Adaptive Bridge Composite Quantile Regression with Ordinal Data | ||
| 260 | |b جامعة القادسية - كلية الادارة والاقتصاد |c 2023 | ||
| 300 | |a 267 - 275 | ||
| 336 | |a بحوث ومقالات |b Article | ||
| 520 | |b Selecting active variables for a QR model is difficult. Selecting the right group of predictors often improves prediction accuracy. To improve scientific understanding, choose a smaller subset. Several methods have been presented to find the active subset. Estimating model parameters aims to find the best estimators for accurate predictions. Estimating all the parameters in the high-dimensional data request yields a weak prediction with large correlations between independent variables, resulting in incorrect findings. Variable selection (V.S) is a key challenge in modelling high-dimensional data. Linear QR selection variables and estimation are studied using the Bayesian hierarchical approach. Regularization bridge and ordinal composite quantile regression are our specialities. This work proposes a Bayesian reciprocal adaptive bridge composite quantile regression for ordinal variable selection and estimation. A new Gibbs sampling approach is developed for comprehensive conditional posterior distributions. We look at how Bayesian reciprocal adaptive bridge composite quantile regression for ordinal data (BrABCQRO) stacks up against other Bayesian and non-Bayesian approaches. The posterior, prior, and conditional distributions are all talked about together. For full conditional posterior distributions, a new Gibbs sampling method is created. A real-world example and many simulation examples show that the suggested methods often work better than standard ones. | ||
| 653 | |a التحليل الإحصائي |a الإحصاء التطبيقي |a الانحدار الكمي | ||
| 692 | |b Reciprocal Adaptive Bridge |b Composite Quantile Regression |b Gibbs Sampler |b Ordinal Data | ||
| 700 | |9 710220 |a Al-Saadi, Zahraa Yusif Abbas |e Co-Author | ||
| 773 | |4 الاقتصاد |4 إدارة الأعمال |6 Economics |6 Business |c 025 |e Al-Qadisiyah Journal for Administrative & Economic Sciences |f Maǧallaẗ al-qādisiyyaẗ li-l-ʻulūm al-idāriyyaẗ wa-al-iqtiṣādiyyaẗ |l 004 |m مج25, ع4 |o 0478 |s مجلة القادسية للعلوم الإدارية والاقتصادية |v 025 |x 1816-9171 | ||
| 856 | |u 0478-025-004-025.pdf | ||
| 930 | |d n |p y |q n | ||
| 995 | |a EcoLink | ||
| 999 | |c 1526818 |d 1526818 | ||
عناصر مشابهة
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Bayesian Reciprocal Bridge Regression for Ordinal Models with an Application
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Simulation Study for the Bayesian Reciprocal Adaptive Lasso Quantile Regression
بواسطة: Lafta, Zahraa Awaid منشور: (2022) -
Bayesian Ridge and Reciprocal Ridge: A Comparative Study
بواسطة: Alhamzawi, Rahim منشور: (2024) -
Bayesian Lasso in Quantile Regression with a New Prior
بواسطة: Al-Husseini, Fadel Hamid Hadi منشور: (2021) -
Employing the Bayesian Elastic Net in Quantile Regression with an Application
بواسطة: Almusaedi, Muntadher Hashim Mnati منشور: (2021)
